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Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte scale - Prior experience with Rust

Synthesia is looking for a Staff Research Scientist Interactive Avatars to lead research on multimodal diffusion models for natural real-time avatar interactions.

Perplexity is looking for a Machine Learning Engineer to develop search, retrieval, LLM training, and multi-agent systems.

Perplexity is looking for a Senior QA Web Engineer to test web products, identify issues, and maintain quality across product experiences.

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools. As a Staff Engineer you will own the technical design and delivery for two areas: AI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team. RESPONSIBILITIES Technical Leadership and Architecture - Set technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap - Turn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions - Establish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt - Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools - Design reliable, scalable infrastructure for hosting AI agents and developer tools - Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit - Work with the Senior Manager and the team's Principal engineers to align technical decisions with business goals Systems Design and Implementation - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days - Build systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization - Set and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management - Design integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Take part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling Strategic Impact and Innovation - Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build - Define how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction - Improve AI tool performance, cost efficiency, and developer experience through architectural improvements - Contribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them - Lead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards Leadership and Mentorship - Mentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices - Lead design reviews and raise the quality of design and code reviews across the team - Create reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on - Help the team turn good individual AI-assisted engineering practice into shared workflows and controls - This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed. QUALIFICATIONS REQUIRED - 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale - Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Track record of designing and building scalable distributed systems and developer-facing platforms - Production experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience designing developer tools, platform systems, or internal tools that other teams rely on - Track record of clarifying requirements and constraints with stakeholders before committing to a design - Track record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority - Strong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs - Clear written and spoken communication suited to a remote, async-first company - Track record of mentoring other experienced engineers - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience evolving an internal platform or tool into a widely adopted, production-grade service - Knowledge of security, compliance, and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Build context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date - Meet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Get hands-on with the team's services and ship a useful production change - Shadow on-call and learn the operational profile of the team's services - Work with the Senior Manager to agree on initial technical priorities FIRST 90 DAYS - Lead the technical framing and delivery plan for one significant problem, from requirements through to production - Document the architecture, technology choices, and integration patterns for that work, including ADRs - Ship a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant) - Contribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management - Lead design reviews for your area of the roadmap and begin mentoring other engineers - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker - Deliver at least one material outcome that spans multiple teams or systems - Have multiple production AI tools demonstrating value across Docker's engineering organization - Help build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction - Define and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact - Grow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people Docker considers sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $170,350 – $275,550 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: United States; Canada Workplace: OnSite WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities - Build and maintain data pipelines for SFT, preference, and RL post-training data. - Own dataset quality, versioning, and reproducibility. - Turn research data recipes into production-grade, reusable components. - Scale model inference for data generation and model-based grading. - Design data formats and schemas that keep post-training datasets consistent and efficient to train on. - Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications - Strong software engineering skills. - Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. - Track record of running distributed data processing and model inference at scale. - Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour. - Excellent communication skills. This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Europe; New York; Toronto Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Key Overview: As a Member of Technical Staff in Post-Training, you will train our large language models (LLMs) with reinforcement learning and develop methods that help them generalize beyond the distribution they were trained on. You will design the training recipes, environments, and evaluations that tell us whether a model has truly learned a skill or has only fitted its training tasks, and turn what works into the recipes behind our production models. You will work closely with the post-training data infrastructure, evaluation, and pre-training teams. Key Responsibilities - Design, run, and analyse large-scale RL post-training experiments (e.g., RLHF, RL from verifiable rewards). - Research and develop methods that improve out-of-distribution generalization, such as reward design, environment and task diversity, curricula, and regularization. - Build held-out evaluations that measure generalization to unseen tasks, domains, and formats, and that catch reward hacking and benchmark overfitting. - Diagnose training dynamics and failure modes, including instability, reward over-optimization, and capability regressions. - Turn successful research into robust, reproducible training recipes for production models. Qualifications - Strong research and software engineering skills, with hands-on experience training LLMs. - Experience applying reinforcement learning to LLMs (e.g., PPO, GRPO, RLHF, RLVR), ideally at scale. - Track record of work on generalization, robustness, or distribution shift, through publications or shipped models. - Rigorous experimental practice: clean ablations, careful controls, and sound conclusions from noisy results. - Experience with distributed training (e.g., JAX, PyTorch, FSDP, Megatron) is a plus. - Excellent communication skills. - Deep understanding of data quality principles and best practices: demonstrates willingness to dive deep into data while possessing strong intuition for assessing the quality of datasets and anticipating how different data characteristics will impact model training outcomes. Working Location This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

• Готовность к глубоко hands-on роли. • Определять стратегию и погружаться в проблемы клиентов.

Shield AI is looking for a Staff IT Systems Engineer to lead regional ICT operations, infrastructure, cloud services, security controls, and compliance.

Shield AI is looking for a Senior Staff Network Engineer to define and evolve secure, scalable, and resilient network architecture.

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $310,000 — $360,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Remote - United States What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $225,000 — $265,000 USD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Runway is looking for a member of the product staff for agents to lead end-to-end development of agent products, improve agent quality, and launch capabilities.

Location: Toronto; Montreal Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! About the role We're hiring a Chief of Staff to keep Cohere's AI organization running at full speed. You'll report to and support the Chief AI Officer and work to bridge across all teams and functions at Cohere (including research, modelling, product, delivery, security, sales and operations). In any given quarter, the org ships new AI product demos and releases, customer pilots and scaled solutions, security updates, often across regions and time zones. Your job is to make sure the right work priorities win when everything feels urgent, that our plans turn into high-quality shipped work, and that our Chief AI Officer can focus on leading instead of firefighting. Much of this is operational: the planning calendar, the budget, the headcount plan, the weekly business reviews, the communication strategy (internal and external), the cross-functional handoffs. Your role is the operating rhythm of the org: meetings, priorities, plans, and the decisions that come out of them. You will be a member of an experienced, high-performing and supportive leadership team. What you'll own Own the operating rhythm and planning: annual and quarterly planning, goal-setting, and the weekly and monthly business reviews. Drive budget and headcount planning against the slate, and keep both honest as priorities shift mid-quarter. Keep major programs from colliding or stalling across research, modelling, product, delivery, and security. Be the person teams come to when it isn't clear who owns a decision, or how to navigate trade-offs. Be the connective tissue between the Chief AI Officer’s org and the rest of the company: cross-functional planning with product, engineering, security, and finance, so the org's commitments are realistic and its dependencies are visible. Own and lead special projects: Lead the things that don't fit neatly on any one team's plate: a reorg, a new partnership, a flagship research event, an org-wide planning week. Own them end to end. Who you are You have 12+ years of operating experience, with real time inside an AI/ML organization in a Chief of Staff, business operations, or senior program-operations seat. You know how to partner with teams shipping fast & often to high-stakes organizations, and you know how to change course with agility when needed. You understand how AI actually works—at the level of someone who's done it rather than managed it from a distance. You can talk credibly about how a model turns into a product, what data requirements demand from both research and engineering, and where delivery motions usually break. You're fluent in the numbers. Model performance metrics, data pipeline throughput, budget-to-impact. You don't have to run every program yourself. You do have to understand them well enough that the people who run them respect your judgment. You hold strategy and execution in the same hand. You can sit in a planning conversation with the Chief AI Officer in the morning and chase down a stuck deliverable in the afternoon. You thrive in a fast-paced environment, you handle ambiguity with curiosity and confidence, you stay calm when it's messy. You have a track record of bringing order to a fast, complex org without grinding it to a halt. You are an outstanding communicator and know how to wield soft power. Clear writing, straight talk, the ability to influence teams and individuals, and the executive presence to represent the Chief AI Officer in high-stakes conversations. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Bengaluru, Karnataka, India, APAC From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role We’re looking for a Staff Technical Writer to write and edit enterprise documentation that empowers our customers to use Fivetran and understand how our data warehouse, database, and data lake products work. You’ll collaborate with engineers, product managers, support engineers, and other technical writers. You join a friendly team of technical writers distributed among our international offices. This is a full-time position based out of our Bangalore office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Documentation-as-code tools, including Markdown, Git, GitHub, and CI/CD workflows Data platforms such as Snowflake, Databricks, and BigQuery Cloud storage services such as Amazon S3, ADLS, and GCS Collaboration and project management tools such as Jira and Slack What You’ll Do Create and maintain clear, accurate product documentation and release notes that help customers succeed. Review and refine customer-facing content, including error messages and UI text. Use a docs-as-code approach to co-author documentation with engineers, product managers, and contributors across the company. Improve existing documentation by ensuring technical accuracy, clarity, and consistency. Collaborate with a global writing team to define and evolve documentation standards, style, and terminology. Partner with engineers, SMEs, and cross-functional teams to deliver best-in-class technical documentation. Contribute to style guides, templates, and other shared resources that raise the bar for all company content. Act as a writing resource for other teams, helping improve content quality across the organization. Skills We’re Looking For Extensive expertise in data warehouse and data lake documentation: 8+ years of experience documenting data warehouses, databases, data lakes, and cloud applications for a US-centric audience. Deep technical knowledge: Experience with complex data lake and data warehouse technologies, cloud platforms (AWS, Azure, GCP), data pipelines (ETL/ELT), and replication techniques. Scripting, automation, and AI proficiency: Skilled at leveraging scripting, automation, and AI tools to streamline documentation workflows and enhance technical content delivery. Exceptional communication skills : Proven ability to craft clear, concise, and accurate documentation; strong technical editing abilities; impeccable grammar; and consistent application of style guides. Documentation leadership: Expertise in content planning, creation, and review processes, with a track record of implementing best practices that elevate documentation quality. Project management and organizational skills: Experience leading documentation projects, mentoring writers, managing competing priorities, and adapting to change while delivering high-quality results. Collaboration and customer focus: Strong history of working with engineers, writers, and globally distributed teams, translating customer needs into improved documentation that drives customer success. Bonus Skills​ Experience working at technology companies with globally distributed technical writing teams documenting enterprise-grade products or services. Understanding of the nuances of complex documentation lifecycles and experience working in an Agile environment. Experience working in a docs-as-code environment, GitHub, Markdown, CLI, and HTML. Understanding of cloud object storage, metadata catalogs such as AWS Glue and Unity Catalog, and open table formats such as Apache Iceberg and Delta Lake. Experience documenting configuration and deployment workflows for containerization and orchestration platforms such as Docker, Podman, and Kubernetes. # LI-HYBRID #LI-DB1 Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

OKX is looking for a Senior Staff Software Engineer to design and operate high-scale payment APIs and distributed services while ensuring transaction correctness and mentoring engineers.

Factory is looking for a Member of Deployed Staff Applied AI to lead enterprise deployments and drive product adoption.

Location: Paris Workplace: Remote ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM You will be a part of a team of 5 engineers, working on the gaming backend platform. This team collaborates closely with all departments of the company, including Core Gaming, Live Gaming and Engineering & Data. Our 'Core' games team supports internal and external studios worldwide in creating, developing, and launching new hit games, whilst our 'Live' games team focuses on delivering higher engagement on our existing and successful games. The Engineering & Data team builds innovative tech products and platforms to support the growth of their gaming and consumer apps. This team is a crucial part of Voodoo’s transition from Hyper-Casual games to Hybrid, Casual & Mid-Core. The backend platform has helped big titles like Mob Control https://apps.apple.com/us/app/mob-control/id1562817072 & Block Jam 3D https://play.google.com/store/apps/details?id=com.partyup.blockjam&hl=en_US achieve amazing growth. In the next phase of evolution, we want to scale this platform to our upcoming promising titles. The objective is to scale the most common features as well as develop new features based on studios'. This position can be fully remote in any EU country. ROLE You will work on the backend platform supporting highly scalable mobile games, played by millions of people every day. You will work closely with client-developers & game designers starting from feature design to delivery, validation, and iteration. The responsibilities are cross-functional, ranging from infrastructure, API design & coding all the way to client-side integration (we are using Golang). To succeed in this role, you will need to have passion for everything you do. You love to write code that scales to millions of users, are skilled at requirements gathering, champion new tech initiatives & leverage existing solutions. - 7+ years of backend development experience - Strong knowledge of computer science fundamentals - Extreme fluency in Golang - Mastery of SQL and NoSQL - Background in high-scale systems - Understanding of Unix-like environments - Experience working in cross-functional agile teams PROFILE - Strong analytical skills with a track record of solving complex problems related to scalability, performance, and integration in high-stakes environments. - Excellent interpersonal and communication skills, capable of influencing teams and interfacing effectively with various stakeholders. - Ability to be self sufficient and work autonomously. - A deep interest in game development is a plus. BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office